Artificial intelligence–enhanced electrocardiography for identifying subclinical left ventricular dysfunction in hypertensive individuals: a comprehensive clinical evaluation

AI-ECG accurately detects GLS-defined subclinical LV dysfunction in hypertensive adults and may serve as an accessible tool for early risk stratification in routine clinical settings.

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Publication Details

Journal
Frontiers in Cardiovascular Medicine
Published
2026-03-03
DOI
https://doi.org/10.3389/fcvm.2026.1761335
Primary Topic
Cardiovascular Function and Risk Factors
Type
article
Field-Weighted Citation Impact
0.00
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article

Artificial intelligence–enhanced electrocardiography for identifying subclinical left ventricular dysfunction in hypertensive individuals: a comprehensive clinical evaluation

Muhammet Fatih Bayraktar
Frontiers in Cardiovascular Medicine
Cardiovascular Function and Risk Factors
article

Artificial intelligence–enhanced electrocardiography for identifying subclinical left ventricular dysfunction in hypertensive individuals: a comprehensive clinical evaluation

Muhammet Fatih Bayraktar
article en

Abstract

AI-ECG accurately detects GLS-defined subclinical LV dysfunction in hypertensive adults and may serve as an accessible tool for early risk stratification in routine clinical settings.

Frontiers in Cardiovascular MedicineVol. 13
Bolu Abant İzzet Baysal University (TR)
Openalex Percentile: Top 42%
Cardiovascular Function and Risk Factors
DOIOpen Access PDFOpenAlex
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Artificial intelligence–enhanced electrocardiography for identifying subclinical left ventricular dysfunction in hypertensive individuals: a comprehensive clinical evaluation — Muhammet Fatih Bayraktar · Frontiers in Cardiovascular Medicine (2026) | TGRS Research Map | TGRS